COMP SCI 861
THEORETICAL FOUNDATIONS OF MACHINE LEARNING
Advanced mathematical theory and methods of machine learning. Statistical learning theory, Vapnik-Chevronenkis Theory, model selection, high-dimensional models, nonparametric methods, probabilistic analysis, optimization, learning paradigms.
Prerequisites & course information
Requisites: E C E/COMP SCI 761 or E C E 830 Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2025
Sources
Catalogue variants
- THEORETICAL FOUNDATIONS OF MACHINE LEARNING · 3 credits.